Top Remote Machine Learning Jobs in Milwaukee, WI

Develop optimization algorithms for ad personalization, integrate ML model predictions, translate findings for stakeholders, and A/B test features.

As a Principal Data Scientist, you will analyze complex data, create measurement techniques, collaborate with teams, and develop models to enhance Zillow Rentals' marketplace performance.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

The Machine Learning Engineer will design, develop, and deploy ML models using Google Cloud tools, focusing on Document AI and Vertex AI, ensuring scalable applications and efficient performance.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

As a Senior Machine Learning Engineer, you'll design and implement deep learning models and robust infrastructures for clinical applications, particularly in computer vision for dental conditions.

The Analytics Engineer will lead analytics initiatives for live events at Netflix, where they’ll define metrics, build reporting tools, and drive strategic insights to improve viewer engagement and monetization.

Design and implement a perception system for autonomous vehicles, focusing on data integration from various sensors and ensuring safe operation.

As a Senior Machine Learning Engineer, you'll develop and deploy AI-driven products, build robust ML models, and collaborate with teams to enhance clinical research using advanced AI solutions.

The Lead Machine Learning Engineer will develop scalable ML systems for optimizing advertising performance, collaborating with global teams and applying advanced ML techniques.

Build and optimize recommendation systems, deploy ML models for personalization, enhance data pipelines, and run A/B tests to drive business growth.

The Senior Machine Learning Engineer will develop and deploy ML models for personalizing user experiences and optimizing content discovery, driving significant revenue growth.

Lead the design, deployment, and scaling of machine learning systems for real-time user recommendations, improving engagement and revenue at scale.

The Lead ML Engineer will design and deploy complex ML systems to optimize ad performance, working with global teams to enhance user engagement and drive revenue.

As a Machine Learning Engineer, you will design, build, and optimize ML models for ad ranking, bidding, and measurements, ensuring effectiveness across Reddit's advertising solutions.

Lead the architecture and development of Reddit's ML Feature Platform, overseeing real-time feature store design, team mentorship, and infrastructure optimization.

As a Senior Machine Learning Engineer, you will design, implement, and optimize ML models for ad ranking and bidding, driving value for Reddit's advertisers.

As a Software Engineer for ML Feature Platform at Reddit, you'll architect and maintain infrastructure for ML features affecting user engagement. Responsibilities include working with large-scale systems, coding in Python, Scala, and Golang, and utilizing Kubernetes and big data technologies.

Lead technical direction for AI across products, architect RAG services, mentor engineers, and ensure compliance in AI usage.

The Lead Product Manager will define and execute product strategy for Machine Learning at ClassPass, collaborating with teams to enhance business through ML applications. Responsibilities include managing product roadmap, analyzing data products, and coordinating with cross-functional teams for successful rollouts.

Lead the development of the Wildfire Fuel Detection Model using ML techniques and geospatial data, collaborating with teams to ensure accuracy and robustness. Mentor engineers and drive architectural decisions.

Lead machine learning platform strategy, scale ML infrastructure, mentor engineers, and drive cross-functional initiatives to enhance product features.

Design and implement machine learning models to improve Risk and Fraud detection systems. Lead technical strategy and partner with operations to address rapidly evolving challenges.